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Enhancing Large Urban Photo Collections with 3D Ladar and GIS Data
Parallel abstracts
Recent work in computer vision has demonstrated the potential to automatically recover camera and scene geometry from large collections of uncooperatively-collected photos. At the same time, aerial ladar and Geographic Information System (GIS) data are becoming more readily accessible. In this paper, we present a system for fusing these data sources in order to transfer 3D and GIS information into outdoor urban imagery. Applying this system to 1000+ pictures shot of the lower Manhattan skyline and the Statue of Liberty, four proof-ofconcept examples of geometry-based photo enhancement are presented which are difficult to perform via conventional image processing: feature annotation, image-based querying, photo segmentation and city image retrieval. In each example, high-level knowledge projects from 3D worldspace into georegistered 2D image planes and/or propagates between different photos. Such automatic capabilities lay the groundwork for future real-time labeling of imagery shot in complex city environments by mobile smart phones.